Neuromodulation of Premotor and Posterior Parietal Cortices For

Article Vol. 6, No. 4 / Oct-Dec 2020 /p. 18-26/ PPCR Journal

Neuromodulation of premotor and posterior parietal cortices for enhancing explicit motor sequence learning in healthy individuals: a randomized, sham-controlled crossover trial

C. Russo*1, MI. Souza Carneiro1, G. Vallar1,2, N. Bolognini1,2 1Department of Psychology & NeuroMi – Milan Center for Neuroscience, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126, Milan, Italy. 2Laboratory of Neuropsychology, IRCCS Istituto Auxologico, Via Mercalli 32, 20122, Milan, Italy. *Corresponding authors: Cristina Russo. Email: [email protected] Received November 11, 2020; accepted January 23, 2020; published February 14 ,2021.

Abstract: Background: Anodal transcranial Direct Current Stimulation (tDCS) has been shown to be effective in improving human motor learning when applied over the contralateral primary motor cortex (M1). However, the stimulation of other cortical areas, such as the posterior parietal (PPC) and premotor (PMC) cortices, may be also beneficial. Methods: The present study (crossover design) investigated the effects of tDCS applied over PPC, PMC, and M1 on the acquisition and retention of a new motor skill, and on the generalization of such learned skill in healthy individuals. During a sequential finger-tapping task (FTT), performed with the non-dominant (left) hand, participants received real or sham anodal tDCS (1.5 mA, 20 min) over PPC, PMC, and the M1 of the right hemisphere. Explicit motor sequence learning was measured online (during the training with tDCS; primary outcome) and 24 hours after tDCS (retention, secondary outcome). A new, untrained, sequence was used to assess generalization effects (secondary outcome). Results: Anodal tDCS of M1 improved both online learning and retention. PMC tDCS facilitated the generalization of the learning effect to the untrained motor sequence. In contrast, neuromodulation of the PPC does not influence motor sequence learning. Conclusions: These findings show that, in addition to M1, higher-order associative cortical regions (PMC and PPC) are involved in explicit online motor sequence learning, retention and generalization playing different roles, as indicated by the differential modulatory effects of anodal tDCS.

Keywords: tDCS, motor sequence learning, motor cortex, premotor cortex, parietal cortex.

DOI: http://dx.doi.org/10.21801/ppcrj.2020.64.3

INTRODUCTION stimulation) or hyperpolarizes (cathodal stimulation) Transcranial Direct Current Stimulation (tDCS) is a well- neuronal membranes at a subthreshold level, changing known non-invasive brain stimulation technique, the likelihood of neuronal firing. While stimulation of widely used to modulate brain activity and behavior. short duration (several seconds or few minutes) is able Through a pair of electrodes placed over the scalp, a to induce short-lasting and reversible effects, several weak (usually 1-2 mA) direct electrical current is minutes of tDCS induce longer lasting effects, which delivered to the brain, modulating cortical excitability in remain stable after the stimulation has ended (Nitsche a reversible and painless way. Cortical excitability et al., 2008). changes are polarity-specific: tDCS depolarizes (anodal Vol. 6, No. 4 / Oct-Dec 2020 /p. 18-26/ PPCR Journal

Cortical excitability changes induced by tDCS can drive generalization of learning has been recently long-term shifts that rely on rearrangements of neural acknowledged. We address this issue in healthy areas and are also usually accompanied by the individuals, exploring the modulatory effects of a single strengthening of synaptic plasticity processes, reflecting application of tDCS delivered to PPC and PMC, as well as long-term potentiation (LTP). Since LTP-like processes M1 in different sessions (crossover design), on motor are thought to represent the physiological basis of sequence learning, which was measured with the learning, it has been hypothesized that tDCS could finger-tapping task (FTT). represent an effective tool to prime, boost or even guide learning via a sort of associative plasticity (Bolognini, MATERIALS AND METHODS Pascual-Leone, & Fregni, 2009). TDCS has been extensively applied to facilitate learning, especially in Participants the motor domain. The prevailing approach involves the Thirty-three healthy individuals (Mean age=23.5 years, stimulation of the primary motor cortex (M1), known to Standard Deviation, SD=± 2.3; 30 females), took part in be the final common pathway of movement control. The this study. Participants were mostly undergraduate majority of studies have applied anodal tDCS over M1, students, recruited through advertisements in printed using different motor learning paradigms, showing its and digital media published at the University of Milano- effectiveness in improving motor learning processes Bicocca and in the neighborhood. Individuals were both in healthy individuals and in stroke patients with included according to the following criteria: i) No motor deficits (Buch et al., 2017). history or clinical evidence of diseases, including The almost exclusive emphasis on M1 may be due psychiatric or neurological disorders; ii) No history of to the easiness of the target, in terms of cortical dependence and/or substance abuse; iii) No use of localization and measurable effects of stimulation. medications affecting the central nervous system; iv) No Notwithstanding, other cortical areas, such as the contraindication to non-invasive brain stimulation premotor cortex (PMC) and the posterior parietal (Rossi et al., 2009); v) right-handedness, as assessed cortex (PPC), may be also involved at different stages of through the Edinburgh Handedness Inventory motor learning, influencing planning, sensorimotor (Oldfield, 1971). All participants gave their written integration and consolidation (Nudo, 2003). informed consent to participate in the study, which was A specific type of motor learning is motor sequence carried out according to the guidelines of the learning, which involves executing a sequence Declaration of Helsinki and approved by the Ethical effortlessly, through repeated practice, as a unit (Dahms Committee of the University of Milano-Bicocca. et al., 2020). As a multilevel process, motor sequence learning involves different, though related, Study design mechanisms: processes driving improvements during A randomized, sham-controlled, crossover trial was practice (online learning), and processes driving performed. By using a crossover design, each stabilization over time or improvement between participant received anodal tDCS to M1, PPC and PMC, sessions (retention) (Robertson & Cohen, 2006). In as well as a sham stimulation (to which both the addition, learning is expected to be specific to the participant and the experimenter were blinded), so that trained task, with little to no improvements in untrained each served as his/her own control. Hence, all the new tasks. A distributed network of cortical and participants underwent 4 different tDCS sessions, subcortical brain circuits is involved in motor sequence separated by a wash-out period of 24 hours, in order to learning. This includes M1, different frontal areas (PMC, minimize carry-over effects (Monte-Silva et al., 2013). supplementary motor area and prefrontal cortex), PPC, The order of the tDCS sessions was randomized across the basal ganglia and the cerebellum. participants. The random allocation sequence was Given these premises, it is likely that, beyond M1, achieved with a computer generating the the electrical stimulation of other cortical areas, such as randomization list. PMC and PPC, may also influence motor sequence learning. To the best of our knowledge, no study has so Finger Tapping Task far performed a direct comparison of tDCS effects on explicit motor sequence learning, with the stimulation A sequential finger-tapping task (FTT) (Zimerman et al., being applied over different cortical areas, while the 2012) was executed: during each session, participants need of a better understanding of tDCS effects on the were trained to perform a sequential digit pressing of a

Vol. 6, No. 4 / Oct-Dec 2020 /p. 18-26/ PPCR Journal fixed 9-element sequence (e.g., 2-4-3-1-2-1-3-4-2) on a During sham tDCS, the same parameters of the active 4-button keyboard using their non-dominant left hand. stimulation were used, but the stimulator was turned The number sequence was displayed over a computer off after 30 sec. This ensures participants an itching screen with each number representing a finger of the sensation at the beginning of tDCS, while no effective left hand: little (1), ring (2), middle (3), and index finger stimulation was delivered, thus allowing a successful (4). The E-Prime software (version 2.0 Psychology blinding for real vs sham stimulation (Gandiga et al., Software Tools) was used to present the to-be-learnt 2006). The target area for the placebo stimulation was digit sequences, recording participants’ responses. randomly defined. Therefore, participants were blinded Participants were instructed to perform the FTT, by to the real/sham intervention delivered and somewhat using their left hand, as accurately and rapidly as blinded even respect to the area (it is difficult for a possible. Participants received instructions not to subject to distinguish whether the anode is placed over correct their response in case of error, rather to M1 or PMC). The experimenter had to know over which continue the task with no pause (e.g., Tecchio et al., area tDCS had to be applied, but he/she was blind with 2010). After each button press, an asterisk mark respect to the stimulation delivered. Indeed, the appeared below each number of the digit sequence, real/sham modes of the tDCS device were activated independently of the correctness of the pressed button. through the use of codes, set and then saved by the The task required to reproduce the entire 9-element principal investigator (N.B.), who did not participate in sequence correctly; consequently, the performed data collection. This method has been shown to be sequence was incorrect if it contained even a single reliable for keeping both the experimenter and the wrong press. No feedback regarding accuracy was participant blinded to sham and real tDCS (e.g., provided. From the FTT, two variables were extracted Bolognini et al., 2013). to assess motor learning: (i) the number of correct sequences reproduced in a block of practice and (ii) the Experimental procedure number of total sequences performed in the same block. Participants underwent 4 training sessions during These two variables were then used to assess our which, concomitant to the FTT, real or sham anodal primary outcome: online learning (performance tDCS was delivered over the right cortex: (i) PPC; (ii) improvements during the task), as well secondary PMC; (iii) M1; (iv) Sham tDCS, randomly applied over outcomes: retention (performance improvements in the right PPC, PMC or M1. the trained sequence after 24 hours) and generalization The presence of adverse effects related to the (performance improvements during the execution of a stimulation was monitored with an ad-hoc new, different, sequence comparable to the trained questionnaire administered at the end of every tDCS sequence) (Censor et al., 2012). session (Brunoni et al., 2011). Participants performed the FTT in sessions Transcranial Direct Current Stimulation comprised by 2 phases: (i) training and (ii) post- TDCS was delivered by a battery-driven, constant training. During the training phase, participants were current stimulator (BrainStim, EMS, Bologna, Italy, instructed to repeatedly perform a given target http://brainstim.it/), using two electrodes (5 x 5 cm), sequence for 5 blocks of 3 min each, with 2 min of break covered by saline-soaked sponges. Direct electric between them (Zimerman et al., 2012) while receiving current was applied with an intensity of 1.5 mA for 20 tDCS. At the post-training phase, participants were min (fade-in/fade-out phases=8 sec), following current presented with a new (different) sequence in a single safety data (Antal et al., 2017). In a crossover design, block lasting 3 min. Such sequence was comparable in active tDCS was applied over 3 different cortical areas of terms of complexity with the trained one (Zimerman et the right hemisphere located by using the 10/20 al., 2012). Overall, the FTT lasted 25 min. Twenty-four electroencephalography system: (i) PPC: the anode was hours after the end of tDCS (FU24), that is, immediately placed over P4; (ii) PMC: the anode was placed over F4, before the beginning of the next session, participants and (iii) M1: the anode was placed over C4. In all cases, underwent a retention test: they were asked again to the reference electrode (cathode) was placed over the perform the target, trained sequence, for a single block contralateral (left) supraorbital area. In the sham of 3 min. condition, tDCS montage was the same of the real conditions (i.e., anode over right P4 or F4 or C4 and the reference electrode over the left supraorbital area).

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Statistical analyses from Blocks 2 (p=.09), 4 (p=.24), and 5 (p=.2). The tDCS Statistical analyses were performed using Statistica for X Blocks interaction [F(12,38)=1.5, p=.13, η2p=.04] was not Windows, release 10 (StatSoft). Significance was set at significant. alpha=.05; main effects and interactions were further explored by means of Newman-Keuls correction. Total (correct plus incorrect) sequences performed Normality of all data was assessed by the Shapiro-Wilk The rm-ANOVA revealed a significant tDCS X Blocks test. Then, since data did not violate normality (p>.05), interaction [F(12,38)=1.8, p=.04, η2p=.05], as well as a main repeated measures Analyses of Variance (rm-ANOVAs) effect of Blocks [F(4,12)=37.7, p<.001, η2p=.54], while no were used to analyze tDCS effects on learning. significant effect of the main factor tDCS was found [F(3,96)=2.2, p=.09, η2p=.06]. As shown in Figure 1B, the Primary outcome total number of sequences performed during M1 To assess tDCS effects on online learning, both the stimulation was higher than in other conditions starting number of the correct sequences reproduced and the from the first block of practice (B1=42.8±11.08); the number of total sequences performed (regardless of M1-induced improvement was evident also in Blocks 2 their correctness, i.e. correct plus incorrect) were (B2=44.6±10.86, p=.03), 3 (B3=45±10.51), 4 analyzed via a rm-ANOVA with tDCS (Sham, PPC, PMC and M1) and Blocks (B1, B2, B3, B4, B5) as within- subjects factors.

Secondary outcomes In order to assess tDCS effects on retention, the correct and the total number of sequences performed were both analyzed via a rm-ANOVA with tDCS and Time (B5 - last block of learning, and FU24 - retention test after 24 hours) as main factors. To assess tDCS effects on generalization, both the correct and the total number of sequences performed were analyzed via a rm-ANOVA with tDCS as within-subjects factor.

RESULTS

Primary outcome: online learning Correct sequences reproduced The rm-ANOVA showed a main effect of tDCS [F(3,96)=3.8, p=.01, η2p=.10]: the number of correct reproduced sequences during the 5 blocks of training was higher under M1 stimulation (Mean number of correct sequences=38, Standard Deviation=±10.22) as compared to all other tDCS conditions, except for PMC (36±8.21, p=.06): Sham (35.3±8.39, p=.04) and PPC (34.4±8.21, p<.01). As compared to sham tDCS, neither PMC nor PPC stimulations improved online performance (p=.55 and .45, respectively; see Figure 1A). The main effect of Blocks [F(4,12)=8.6, p<.001, η2 =.20] showed the typical learning effect: the number p Figure 1. Online learning effects. Number of correct sequences of correct sequences in Blocks 1 (34.6±8.21) and 2 reproduced (A) and number of total sequences performed (B) (35.4±8.04) was significantly lower than that in Blocks of the trained digit sequence during the 5 blocks of learning; 4 (36.8±7.87, p=.01) and 5 (37±7.75, p<.01). The rate of B1=block 1, B2=block 2, B3=block 3, B4=block 4, B5=block 5. correct sequences reproduced in Block 3 (36.2±7.58) Bold lines= within-group differences; *= between-group differences; p<.05. Error bars= SE. was higher than that in Block 1 (p<.01), but not different

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(B4=45.8±11.08), and 5 (B5=46.7±9.99) (p<.01 for comparisons of B3, B4 and B5). During PMC stimulation, the total number of performed sequences significantly increased in Block 2 (B2=41.3±9.25) and was even greater in the following blocks (B3=42.2±8.90; B4=44.4±8.5; B5=44.6±8.39) (p<.01 for comparisons of B2, B3, B4 and B5), as compared to Block 1 (39.3±9.94). During PPC modulation, the increase took place later, starting from Block 4 (B4=42.8±9.24; B5=43.8±8.78) (p<.01 for comparisons of B4 and B5), as compared to the first block of practice (B1=40.7±9.01). Importantly, during sham tDCS, an increase of the total sequences performed was found in Block 3 (43.1±9.76), 4 (43.3±8.79), and 5 (43.8±9.02) (p<.01 for comparisons of B3, B4 and B5), as compared to Block 1 (B1=40.7, SD=±9.53). Block 2 (B2=42.1, SD=±9.47) did not differ from Block 1 (p=.12), as Block 3 did not differ from Block 4 (p=.8) and 5 (p=.7).

Secondary outcome: retention Correct sequences reproduced As shown in Figure 2A, the rm-ANOVA revealed a main effect of tDCS [F(3,96)=4.7, p<.01, η2p=.12], showing better performance after M1 stimulation (40.7±10.11) as compared to sham (37.9±8.1, p=.03) and PPC (37±7.98, p<.01) tDCS. On the other hand, while PMC stimulation (39.8±1.39) did not differ from M1 (p=.38) and sham (p=.09) stimulations, PMC tDCS improved performance as compared to PPC tDCS (p=.04). The main effect of Time [F(1,32)=28, p<.001, η2p=.5] showed a further improvement of correct sequence reproduction after 24 Figure 2. Retention effects. Number of correct sequences hours (FU24=40.6±8.1 vs. B5=37±7.75, p<.01). The reproduces (A) and number of total sequences performed (B) of tDCS X Time interaction [F(3,96)=.7, p=.5, η2p=.02] was not the trained digit sequence in the last block of training vs. 24 hours significant. after; B5= block 5, FU24= follow-up 24 hours after the end of the training. Bold lines= within-group differences; *= between-group differences; p< .05. Error bars= SE. Total (correct plus incorrect) sequences performed The main effect of tDCS [F(3,96)=3.8, p=.01, η2p=.10] showed a better performance after M1 tDCS stimulation improved the reproduction of the new, (47.5±10.22), as compared to PMC (45.5±8.1, p=.048), untrained, digit sequence (37.3±10.30) as compared to PPC (44.5±8.39, p=.02), and sham (44.7±8.79, p=.01) all other conditions (p<.01): Sham (28±9.31), PPC stimulations (see Figure 2B). The main effect of Time (28.3±8.89), and M1 (30.2±9.75). Sham tDCS did not [F(1,32)=11.5, p<.001, η2p=.3] showed a further differ from M1 (p=.24) nor PPC (p=.79) stimulations. improvement after 24 hours (FU24=46.4±8.56), as compared to the last block of practice (B5=44.7±8.1, Total (correct plus incorrect) sequences performed 2 p<.001). The interaction tDCS X Time [F(3,96)=.06, p=.98, The significant effect of tDCS [F(3,93)=9.6, p<.01, η p=.20] η2p<.001] was not significant. showed the facilitatory effect of PMC tDCS (43.6±9.89), which induced a larger generalization effect as Secondary outcome: generalization compared to all other conditions (p<.01): M1 Correct sequences reproduced (40±10.45), PPC (37.7±8.84), and Sham (37.4±8.14). As shown in Figure 3A, the main effect of tDCS Sham tDCS did not differ from M1 (p=.11) nor PPC (p=.85) stimulations (see Figure 3B). [F(3,93)=22.2, p<.01, η2p=.40] showed that PMC

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and retention. Moreover, M1 stimulation facilitates the performance from the very beginning of the practice also in terms of total sequences performed. As for retention, M1 tDCS can further enhance off- line motor sequence learning. In fact, both the rate of the correct sequences reproduced and the total number of sequences performed increased 24 hours after M1 stimulation, at least with respect to sham and PPC tDCS. It is known that excitatory M1 stimulation facilitates motor learning, as assessed through various tasks (e.g., Reis et al., 2009; Stagg et al., 2011). While the underlying neural mechanisms are still under investigation, such effect seems related to long-term potentiation LTP mechanisms and the functioning of N-methyl-D- glutamate (NMDA) receptors. Particularly, since M1 is rich of dopaminergic terminals, an excitatory stimulation would boost LTP processes. Indeed, it has been shown that blocking dopaminergic activity in M1 hampers LTP and, consequently, reduces learning (Molina-Luna et al., 2009). With respect to PMC stimulation, we found intriguing results. While M1 tDCS facilitates online motor sequence learning compared to sham and PPC tDCS, PMC stimulation is placed somehow in between: learning effects (correct reproduced sequence) driven by PMC stimulation are similar to those elicited by M1 tDCS, although they are not different from the performance under sham condition. In terms of total Figure 3. Generalization effects. Number of correct sequences sequences performed, PMC neuromodulation facilitates reproduced (A), and number of total sequences performed (B) for the untrained digit sequence in the post-training phase. *= the performance from the very beginning of the between-group differences; p< .05. Error bars= SE. practice, as M1 tDCS does. The efficacy of PMC stimulation could be related to the role of this area in early learning stages of a motor sequence task (Steele & DISCUSSION Penhune, 2010). Although PMC is bilaterally recruited The present study assessed the effects of anodal tDCS during the early stages of skill learning, there is a more over different fronto-parietal areas (PPC, PMC and M1) prominent activation of the PMC in the right on motor sequence learning (FTT), across various hemisphere (Deiber et al., 1997), which likely reflects components of the learning process: the online the spatial processing necessary for motor acquisition. acquisition of a new skill, its retention and the Indeed, an increased cognitive information processing generalization to a not-trained activity. Overall, our is expected during the early learning stage, as results feature elements of confirmation and novelty: individuals associate sensory cues with correct motor they provide evidence that anodal M1 tDCS facilitates commands (Kantak et al., 2012). Hence, increasing the both online learning and retention, and also activity of the right PMC during motor sequence demonstrated that anodal PMC tDCS promotes learning likely facilitates the establishment of novel generalization, while PPC tDCS does not influence visuo-motor association, with the effect of a widespread motor sequence learning. motor behavior facilitation (more reproduced With respect to M1 stimulation, our results sequences), but this occurs before the storage of the support current evidence. Considering the correct acquisition of a new visuomotor skill, which needs the number of reproduced sequences, it confirmed M1 as a recruitment of left PMC to allow the establishment of the key area of the motor network to be stimulated with learning effect, for improving motor accuracy tDCS to increase both online motor sequence learning (Halsband & Lange, 2006). As for retention, the right

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PMC tDCS has similar effects to those induced by M1 however, the experimenter who applied the stimulation tDCS when the ability to correctly reproduce a digit was not the same who performed the analysis, and FTT sequence is considered. However, PMC stimulation has were computed and extracted by a software, therefore, larger effect than M1 when the global performance, we believe, lowering the risk of such bias. regardless of its accuracy, is considered. Secondly, we compared many conditions, running The main novel finding of our study is represented multiple comparisons, due to the adoption of a by the effects on a new, untrained, motor sequence, crossover design and the need to evaluate the effects which is selectively facilitated by PMC stimulation. over different time-points, with the risk of increasing Current literature shows that the integration of sensory type one error. information into motor commands are assignments of Finally, it should be noted that this study was PMC, which is also involved in movement selection and carried out in our Department of Psychology; therefore, retention (Gremel & Costa, 2013). A long-term practice the sample is mainly composed by female (30 out of 33) results in a faster, effortless and accurate performance young adults (mean age= 23.5 years). It follows that primarily because movements are planned in a motor- both gender and age of our experimental group could center coordinate system, rather than a vision-center represent potential sample biases that may hinder one as in earlier learning stages (Marinelli et al., 2017). external validity of our findings. With respect to gender, Successful consolidation processes include memory to the best of our knowledge, there is no evidence in the association and translocation, which means that literature regarding substantial gender-related recently acquired information are integrated with past difference in motor sequence learning, but they could be experiences, while an anatomical reorganization of in relation to tDCS effects (Thomas et al., 2019). As for memory representation occurs. Here, we may speculate age, an intriguing review (Voelcker-Rehage, 2008) that PMC tDCS can reinforce the memory trace of the pointed out how the decline in motor learning due to learned digit sequence, allowing an effective movement age is task-specific, with a comparable learning of translocation, resulting in the ability to recognize the younger and older adults in low-complexity tasks. On new activity “pattern” and successfully perform it. the other hand, an age-related variability in tDCS effects Finally, PPC tDCS has no effect on motor sequence has been acknowledged (Li et al., 2015). Since age and learning by itself; rather, it seems even detrimental, gender could limit the generalizability of our results, this delaying practice-induced improvements, at least in should prompt future investigation to seek to explore terms of the total amount of sequences reproduced, putative intriguing interactions between age, gender regardless of their correctness. In fact, as compared to and neuromodulation effects on motor sequence sham tDCS, during the PPC stimulation, the learning. performance improvement emerges only at the end of A final note of caution is needed with respect to the training (Block 4), while it appears sooner without tDCS neuromodulation of PMC; tDCS has low spatial focality, (Block 3 during sham tDCS) and it is even anticipated hence it is highly probable that the delivery of tDCS over during M1 and PMC tDCS (Block 2). In addition, also the PMC may have also affected the functioning of retention of the learnt digit sequence, in terms of both neighboring cortical areas, in particular the Dorsolateral correct and overall performance, was significantly Prefrontal Cortex. lower in the PPC condition, as compared to M1 and PMC stimulations. A possible speculation may be that the CONCLUSIONS anodal (excitatory) tDCS applied over the right PPC In conclusion, results of the present exploratory study could interfere with movement planning and learning confirm the efficacy of M1 tDCS on motor sequence by causing an indirect interhemispheric inhibition of the learning, with beneficial effects emerging during the left PPC. training phase and in the long-term. On the other hand, M1 tDCS, as well as PPC tDCS, does not affect the Limitations generalization of the learned skill to a new untrained A main limitation of the present study, given its pilot sequence. PMC tDCS has similar effects as M1 tDCS on nature, is the small size of the sample. Studies involving online learning and retention, but it also has a larger larger samples of participants, with higher statistical facilitatory effect on the generalization of learning. PPC power, are mandatory to confirm and extend the tDCS, instead, does not influence motor sequence present evidence. A possible source of potential bias is learning. Therefore, we found an interesting that the experiment was not blind to the target area; dissociation between M1 and PMC effects: while M1

Vol. 6, No. 4 / Oct-Dec 2020 /p. 18-26/ PPCR Journal plays a main role in promoting online learning and Brunoni AR, Amadera J, Berbel B, Volz MS, Rizzerio BG, Fregni F (2011). A retention, PMC is recruited at a later stage for allowing systematic review on reporting and assessment of adverse effects associated with transcranial direct current stimulation. The the generalization to untrained movements. international journal of neuropsychopharmacology, 14(8), 1133– These suggestive findings may have some 1145. https://doi.org/10.1017/S1461145710001690 important clinical implications: tDCS protocols Buch ER, Santarnecchi E, Antal A, Born J, Celnik PA, Classen J et al. (2017). targeting different cortical areas could be used to Effects of tDCS on motor learning and memory formation: A consensus and critical position paper. 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